This invention pertains generally to the field of knowledge-based computer and processing systems and more particularly, to the field of knowledge management systems, model driven decision support systems, and data and information driven decision support tools for enterprise value enhancement.
The intellectual assets of a corporation are typically three to four times the tangible book value. With roughly 15% of the US workforce employed in the information sector today, the knowledge industry represents 33% of GDP and generates more than 50% of all corporate profits. Knowledge has essentially become the primary ingredient of whatever is made, done, bought and sold. Value creation in the enterprise is thus becoming increasingly dependent on xe2x80x9cknowledge productization,xe2x80x9d which in turn is driven by knowledge activity. Growth, therefore, can be achieved only through increased knowledge activity.
Despite this trend, less than 2% of the number of major corporations grew total shareholder return by more than 35% per year over the last decade, and less than 1% of all companies grew earnings by more than 50% per year over the last five years. One of the major factors responsible for this is the lack of sufficient knowledge management systems for enterprise value enhancement.
Enterprise value enhancement, a business and knowledge management process to dynamically improve enterprise-wide business resultsxe2x80x94and thereby continuously renewing and increasing the fundamental value of the enterprise, has become more challenging than ever before for senior management. The business environment is increasing in complexity and uncertainty, and product and industry life cycles are becoming shorter. Moreover, as the business world becomes more digitally connected, the need for dynamic mass-customized solutions to add value seems to be on the rise. FIG. 1 shows the evolution of value-adding mechanisms over time.
Value creation in the enterprise has thus far been predominantly a passive strategy responding to market movements rather than a proactive strategy pervading all functions and occurring throughout the enterprise by identifying all the opportunities and all the spaces in which to add value. FIG. 2 presents a unique way to visualize the process of value creation, which is in many ways similar to filling a large room with Ping-Pong balls. As demonstrated, different ways of aligning and orienting the balls along the walls of the room yield significantly different counts of balls that can fit the exact same room dimensions. Value creation is dependent upon strategy, and the notion of strategy as xe2x80x9cthe gentle art of re-perceivingxe2x80x9d does make strategy an inherently creative process, but business creativity is much broader in that it encompasses both innovation and entrepreneurship.
Creativity is how value is derived from new ideas and the processes by which those ideas are developed, typically following the commercialization process, the steps of which are outlined in FIG. 3.
The delivery of enterprise value enhancement on an on-going basis with certainty is becoming more difficult in the fast-changing business landscape primarily because value enhancement is still an art rather than a science. The essential contributors and drivers of value enhancement are still the humans with expertise retained within themselves and upon whom a heavy reliance for knowledge transformation is placed, despite great technological advancements. The xe2x80x98fishschoolxe2x80x99 effect, where everyone follows a mission or direction regardless of whether the overall strategic objectives are being met at every step along the way, is ideal for project implementation and is therefore even desired for effective project management. Value enhancement, on the other hand, is essentially a process of continually gathering innovative ideas across the enterprise, integrating them seamlessly with strategic initiatives, and then deploying them through xe2x80x98implementation solutionsxe2x80x99 based on enterprise potential and desired speed, the latter two factors linked to the resources available to the enterprise in question. A value enhancement perspective results in continuously optimized value delivery through all the elements of the value add cube as can be seen in FIG. 4. Enterprise value enhancement is thus a function of strategy, marketing, finance, and the collective application of enterprise creativity and knowledge assembled in a flow designed for continuous renewal and dependent, among other factors, upon flow rates and queues.
Knowledge has been defined as an opinion, idea or theory that has been verified empirically and agreed upon by a community. In a sense, it is defined as a justified, true belief and this view ignores tacit knowledge. Management on the other hand is the cyclical process of planning, organizing, action, control and feedback. Knowledge management is a discipline that promotes an integrated approach to identifying, managing and sharing all of the information assets in the enterprise, including databases, documents, policies and procedures as well as unarticulated expertise and experience resident in individual workers. Knowledge itself is an elusive asset which is why knowledge management, a discipline that manages and improves the organizational learning process, must be baked into the enterprise. The human factor is very critical and knowledge management, for all its importance, is still maturing.
The recent focus of knowledge management systems has been on effective information access that improves and speeds up the learning process, and such systems facilitate the collection, organization and transfer of knowledge aided by search engines, relational and object databases, GroupWare and other technologies. The core component of current knowledge management systems is the knowledge warehouse, and the emphasis is mainly on explicit knowledge. Knowledge, however, in the broadest sense, resides mostly inside people, with their portfolio of know-how, memory of past solutions, understanding of what works well, and their ability to see patterns and come up with fresh solutions that have a high probability of success. An enterprise needs to be well stocked with such tacit knowledge. The need today is for streams of ideas that can continuously enhance value or, in other words, knowledge flow with a focus on value creation.
Enterprise value enhancement, which pertains to the field of knowledge management, enables an entire organization to be collectively engaged in the process of contributing to the knowledge generation, knowledge communication and knowledge distribution process, the essential steps in productizing knowledge, whether for a product or for a service. Knowledge generation is fueled by knowledge communication across the enterprise, and value addition ultimately takes place through the transformation of knowledge activity into offerings, namely through the process of knowledge distribution. Enterprise value enhancement thus depends upon the systematic extraction of explicit and tacit knowledge within the enterprise and its continuous conversion to new, value through the creativity process via highly efficient implementation methodologies eliminating the typical knowledge xe2x80x9csiloingxe2x80x9d effects that tend to take place in corporate settings.
It is estimated that less than one-fifth of all intellectual capital available to an enterprise is actually utilized. The gross under-utilization of this very important knowledge resource occurs for various reasons some of which are sub-optimized organizational structures, lack of systems for capturing creativity, and interspersed xe2x80x98human elementsxe2x80x99 such as the lack of motivation and the presence of ego. Opportunities for innovation, which is invention realized or commercialized, do not emerge from sophisticated analysis of data or from a rearrangement of existing information into different formatsxe2x80x94they emerge from experiences and insights and mostly in environments that encourage creativity. Enterprise value enhancement is about the systematic collective application of enterprise creativity and knowledge leveraged to chart future actions designed to deliver on-going value propositions that result in a continuous maximization of the value of the enterprise over the long term.
What shapes history is the environment, the happenings, and the perceived effects, the environmental dynamics causing the happenings in turn to determine the perceived effects. Based on this model of influences, events and experiences connected by carriers, a value enhancement model is derived as depicted in FIG. 5. The extent and speed of value enhancement within the enterprise is a function of the knowledge activity, i.e. the content, the quality and the speed of knowledge transformation. In other words, value enhancement is dependent upon the generation of knowledge, the communication of knowledge and the distribution of knowledge within and outside the business system of the enterprise, and its seamless integration to the leadership, management, business and distribution systems.
Value enhancement focuses on the enterprise in its entirety rather than only on one specific aspect or area like marketing, finance or strategy, or for only a specific purpose like computing a range of future values. This new multidimensional approach provides a systematic methodology for capturing creativity, enabling knowledge generation, knowledge communication and knowledge distribution, and dynamically re-balancing all of these with the leadership system, organizational design, management system and distribution system of the enterprise. Observed from the value enhancement view, the principles of offering design take on a new perspective (FIGS. 6A and 6B) and the demand creation process (FIG. 7) appears to become a more complex and highly interconnected webxe2x80x94similar to an economic web. Armed with such a value-enhancement perspective leads to a greater understanding of value drivers and perhaps enables one to make appropriate and rapid improvements in the relevant processes and sub-processes. Similarly, the employee contribution chain (FIG. 8) highlights the key elements that drive employee motivation to enable performance at higher levels of employee discretionary effort. Although intuitive to some, these new insights can certainly aid in the value addition process if factored in systematically. In most firms though, management practices do not attempt to go deep enough to understand the value drivers in the total context of the enterprise.
A recent study of market valuations, financial performance over the past five years, and value propositions and strategies of approximately 11,000 publicly listed companies revealed that value-driven companies have some unique characteristics in common. These are (a) exceptional value propositions derived from creativity and trends in the landscape, (b) cohesive organizational structures with efficient knowledge flow enabling near-flawless implementation, and (c) high-sales, high-income or high-earnings growth rates. The first two characteristics led to the third naturally in some cases, but the reverse was not found to be true; moreover, each of these characteristics, for the most part, were found to be independent. Companies with such characteristics are not the well-known companies that we read about frequently but are the cohesive, well-knit companies that have mastered the generation, communication and distribution of knowledge, creating exceptional market values per employee as a result. Market value per employee is an appropriate metric that can easily help determine the net value addition per person employed in the enterprise as discounted by market forcesxe2x80x94and we are already beginning to see how important intellectual capital is becoming and how it is being reflected primarily through market valuations today.
Table 1 depicts the stack rankings of companies with the highest sales growth rate, the highest income growth rates and the highest earnings growth rates, all observed separately. These are derived from the same pool of over 11,000 companies at the end of the second quarter of 1998. Table 2 is a similar stack ranking of high sales, high income and high earnings growth rate companies (this time all three factors combined), leading to a different list. This list yields companies with consistently high market values per employee, and in fact exceeding $1M/person as in end-June 1998. Another set of companies with relatively high market values per employee were among those focused on specific business services by providing unique value propositions. These companies, however, did not necessarily have very high growth rates.
Profit-making and growing companies (as defined here by companies with positive cash flow from operations and with at least a 10% average revenue growth per year over the last three years) represent a mere 20% of the total pool. A market value of $1M/employee, to put in perspective, is three times the average of all profit-making and growing companies and indicates membership in the cream of the population. GE, valued at roughly $300Bxe2x80x94which became the most valuable company in the US surpassing the valuation of Microsoft in mid-1998xe2x80x94has a market value per employee of over $1M; see Table 3. General Motors, by contrast, which is neither in a knowledge-based business nor in a high growth mode, has a market value per employee of less than $0.1M.
The foregoing study leads to the conclusion that there is a definite correlation between the value enhancement characteristics described above and high per employee market valuations. While high valuations are desirable and for many boards the ultimate goal, continuously creating exceptional value propositions and enabling high degrees of knowledge activity and efficient knowledge flow in organizational structures over time is a more difficult task. The model shown in FIG. 9 is a process that would be helpful for managers to follow to enable just that.
Developing business processes without mechanisms to add value is short-term. Similarly, developing corporate strategy without insights is dangerous because it leads to unrealistic plans. Defining purpose, discovering insights and combining the two into strategy is hard enough for many companies which is apparent when we see how competitive forces are shortening life-cycles. Electronic commerce has created a new environment in which new opportunities exist for innovative ways to add value. Strategy formulation as well as knowledge management are still evolving and present somewhat of a puzzle in many organizations even today. An even more complex process, however, is the value enhancement process, which requires creativity resulting from higher levels of knowledge activity and knowledge flow to be the fuel for systematic incremental value addition. By adopting the application methodology of the enterprise value enhancement model, managers can have a useful framework for channeling efforts in the direction of tacit knowledge led value enhancement.
Strategic planning initiatives are an important and critical aspect of an organization""s success, but they still comprise only one of the many decision support tools required for the management of an enterprise. The emotional side of strategy has been ignored too often in spite of the fact that strategy is as much about experimentation as it is about foresight and passion. In many organizations the quest for efficiency drives out experimentation and the ability to listen to the voice of the customer. This is one reason why disruptive technologies have managed to displace so many corporations in their entirety.
Work has been done in the past on developing systems which enable projections pertaining to markets, expected sales, costs, the economy in general, changes in the state of technology, emerging product technology and political influences among others to provide decision support for resource allocation purposes. In these cases also, there is a variety of incomplete and inconsistent information from many different sources that have to be reasoned out and reconciled, and even in the presence of reconciliation rules and the like, these systems merely reorganize data and information for further processing and do not capture the creativity of the enterprise for ultimate conversion into value.
Future values of variables can be determined by some existing enterprise models which include flow relationships, causal relationships, compositional relationships and productivity relationships besides reasoning and reconciliation to create a realistic model of an enterprise. The prior art has addressed some of the problems by creating computer systems to generate plausible recommendations concerning the nature and amount of various resources that are required to supply the enterprise and to identify certain actions appropriate to acquire and develop these resources. The problem is that existing systems are based either on hierarchical models or are meant to enable decision-making regarding resource allocation only, and not for the larger purpose of overall enterprise value enhancement. Moreover, realistic value projections are difficult to make in some cases requiring complex reasoning and reconciliation, and as a result organizations rely heavily on manual processes with primary decision support coming from spreadsheet tools, word processing programs and electronic mail and the reconciliation dependent on the knowledge and expertise of managers.
The prior art has several limitations. While it can handle multiple reasoning, generate certainty factors, map inputs and outputs, and incorporate features of inference expert systems into continuous state feed-forward neural networks, it still cannot capture creativity or direct focus to areas requiring action for value enhancement. Expert systems lack the ability to learn from examples and neural networks find it difficult to deal with explanations. Moreover, expert systems rely primarily on hand-crafted rules as their xe2x80x9csource of knowledgexe2x80x9d. Building an expert system also requires finding a human expert in the problem domain, translating the human""s knowledge into if-then rules, and then debugging the rulebase. Therefore, in some cases, hiring or training additional experts may be less expensive than building expert systems.
Neural networks attempt to emulate the processing patterns of the biological brain and learn primarily by computation of confidence measures. They do not model human intelligence, they do not perform solutions and they do not aim to solve specific problems. Instead, they are designed with a generalized capability to learn and are certainly efficient at linear relationship mappings. However, the real world problems are far more complex and non-linear in relationship and mappings through neural networks can become difficult.
The prior art deals with heuristic learning application programs and its application to retrieval of heuristically documented solutions. These, however, have very limited applications as of date and are used primarily in locating records during a computer-telephony interface, e.g. retrieving medical records during a patient - medical advisor telephony interaction.
The prior art also does not consider the engagement, commitment, expertise and innovative inputs of the field nor does it incorporate any links such as marketing research, enterprise computing systems, knowledge bases and on-line expert advice-giving systems. The prior art also does not include any real time interactive features.
While most systems of the prior art address the problem of determining a future value, computing in a distributed network, or mapping relationships, they are essentially limited in that they allow access to specific databases for specific purposes of computation or reconciliation. The problem, however, is that information of interest lies in a complex combination of dynamic databases, and that there is data and information beyond the warehouse. The enhancement of enterprise value is dependent upon the proper understanding, utilization and integration of that complex combination of information together with the existing knowledge in the enterprise, the creativity of the enterprise and the enterprise model. This is precisely the problem that has not been fully addressed in the prior art. Thus, the creation of a system, method and apparatus for enterprise value enhancement is an advance that would have a wide range of use and application by senior managers.
The extent and speed of value enhancement in an enterprise will increasingly depend upon knowledge activity, by which I mean the content, the quality and the speed of knowledge transformation. In other words, value enhancement depends on the generation of knowledge, the communication of knowledge, and the distribution of knowledge within and outside the business system of the enterprise.
My invention provides a method and a system that focuses on the value enhancement of an enterprise in its entirety rather than on only one specific aspect or area, such as marketing, finance, or strategy. I use a globally networked total solution system that delivers enterprise value enhancement through solution sets most appropriate for execution by specific functions for delivery of enhanced value. A field feedback engine is part of the design of my enterprise value enhancement system and captures and optimizes engagement, commitment and expertise of the field for the best use of the enterprise to maximize value enhancement. Additionally, my inventive system allows for customization and personalization of solutions for enterprise value enhancement to a greater degree than does the prior art.
My value enhancement processing system captures the knowledge generation, communication, and distribution mechanism of the enterprise to speedily roll out solutions for value enhancement. The present invention overcomes the deficiencies of the prior art by delivering automated solutions for value enhancement, as well as tracking and updating results, feedback, and references continuously rather than merely projecting a future value for a given set of conditions or a set of values for the future for a given set of conditions based on preprogrammed rules of reconciliation for specific input queries.
In an exemplary embodiment of my inventive system, I include an input device for interactive input of field feedback via field feedback surveys created by a field feedback survey generator. The field feedback survey generator receives the field feedback and processes, renews, and updates enterprise value enhancement solution surveys based on the field feedback. A switchboard imports data from various databases or multimedia databases into the processing system. I also prefer to include a performance processor that assimilates the field feedback and the data imported by the switchboard to process linkages between the data, form clusters of elemental information, and make appropriate computations, associations, and new linkages. A customer asset valuation processor preferably receives relevant information to dynamically compute customer asset value and assign attributes to the customer assets as necessary. A performance metrics engine monitors metrics and the direction of movement of the metrics, as well as the accuracy of projections of the values of the metrics. My inventive system includes a value enhancement solution generator that receives data from the field feedback survey generator, the switchboard, the performance processor, the customer asset valuation processor, and the performance metrics engine and generates value enhancement solutions based on these data. The solution generator then delivers recommended solutions for value enhancement of the enterprise, with linkages to specific functions. The field feedback survey generator also generates the field feedback surveys used by the input device and updates the field feedback surveys.
My inventive system preferably performs a method of enterprise value enhancement including the steps of creating a value enhancement model of the enterprise based on planning loop structures, the planning loop structures each being a dynamic frame-based model, continuously updating and refining the value enhancement model of the enterprise, and providing a set of causals, logical explanations, and reconciliation rules to cross-link types of enterprise activities to causals, functions, and solutions. The method also includes steps of accepting input from a field survey administrator through an interface, providing a method of generating new field feedback surveys to capture individuals"" knowledge by applying previous field feedback and linking to the types, causals, functions, solutions, and results from those solutions. Further, the method preferably includes accepting input pertaining to an account to determine key solutions for value enhancement as relevant to the account, applying the account specific information to the set of reconciliation rules of linkages between types, causals, functions and solutions, and providing a set of variable solutions customized for at least one of specific target customer accounts, specific target supplier accounts, market segments by type of account, and market segments by type of offering, and for specific functions to be executed in order to enhance overall enterprise value.
Various refinements of the system and the method it performs are also encompassed by my invention. In particular, a particular method can be executed in the planning loop structures including the steps of accepting a user interaction through a user interface, recommending a cost reduction process, determining a scope for higher value added products and services, tracking and determining a potential for movement in various metrics, providing solutions through the user interface to different functional groups in the enterprise, analyzing financial performance, generating new feedback formats, sending field feedback surveys automatically at preset frequencies to update information and current and desired states, collecting new field feedback, inputting the feedback into the performance processor, and generating new enterprise value enhancement solutions through a continuous closed loop process, thus renewing the potential for incremental value creation in successive time periods. Various refinements can be made to the planning loop structure method as well.
With my inventive system and method, productivity, efficiency of value can be enhanced beyond what is possible with prior art systems and methods. This improved enhancement results in part from the more successful capture of tacit knowledge by my system and method.